In the post below, Gene Steuerle of the Peter G. Peterson Foundation discusses the significance of the new Health Affairs releases. In another Health Affairs Blog post, Rudy Penner of the Urban Institute says that the new CMS report once again emphasizes the need for reforming Social Security, Medicare, and Medicaid. ***

I have long been a fan of the work performed by the Office of the Actuary at the Centers for Medicare and Medicaid Services (CMS). Among the finest offices of civil servants anywhere, it provides vital information that is used by almost every health policy analyst and policymaker I know — even though too few acknowledge its achievements. Even though they receive too few resources for tasks at hand. Even though their knowledge doesn’t always rise through the political process to help policymakers.

I also very much appreciate the work that Altarum is performing on breaking down health spending by medical condition. (Truth in reporting: The Peter G. Peterson Foundation, of which I am vice president, recently has been considering a grant to Altarum)

However, I have been asked to go beyond praise to try to provide some value-added to a discussion of two recent reports, “Health Spending Projections through 2018” and “National Health Spending by Medical Condition, 1996-2005.” I want to concentrate on three items: (1) a crucial missing piece of analysis (in technical terms, the input side of the input-output matrix) that is required to better determine both what’s going on and the quality of the predictions; (2) the great limitations of any predictive model, especially one based upon one sector’s trends to the exclusion of others and on the assumption of maintenance of an unsustainable set of policies; and (3) an explanation of why saving in dealing with one medical condition may lead to only limited net saving for the nation’s health budget.

Improving Our Knowledge Of Underlying Trends

For at least two decades now, I have argued strenuously that we need to expand resources, perhaps in the Office of the Actuary, to complete the input-output matrix on national health spending. Crudely speaking, the CMS provides estimates of output, defined as price (p) times quantity (q) of services (sum of p x q). If you assume for ease of explanation that wages (w) to labor (l) comprise most payments received (including wages of scientists, insurers, and administrators, and profits that are reinvested in humans developing newer technology and drugs), then on the opposite side of the ledger, aggregate spending comes close to equaling (sum of w x l).

Why do we want to develop both sets of estimates? For many reasons. For one, as national income accountants know, the complete balance sheet provides many checks on consistency, as numbers must now add up equally on both sides of that sheet. Second, the more complete picture allows us to detect where the growth in payments to individuals lies (e.g., more practical nurses, or more payments to doctors, or more scientists, or higher payments to administrators).

Third, from a policy perspective, it would help us make better judgments about how to adjust payment schedules, such as the Medicare physician payment schedule, and to assess the related issue of how much rapid expansion in some new treatment is driven by large opportunities for individual remuneration. (Take, for example, rapid growth in knee operations or doctors’ owning sleep centers that detect sleep apnea.) Finally, the same balancing would then be required when it comes to making predictions for the future. For instance, in the actuaries’ report, an input-output matrix would have provided a reality check through implied rates of growth in numbers of providers and related workers, as well as their incomes.

The Limitations Of Predictive Models In Health

As the actuaries note well in their report, the predictions they make do not take into account a variety of potential behavioral changes. Indeed, these models (and most economic, not just actuarial, models) are no more reliable than the models that assumed that decades of continual growth in housing prices was sufficient to underpin AAA ratings for mortgage-backed securities.

This is not so much a criticism as a warning. For instance, models that predict past growth on relative constancy in health cost growth above economic growth do not assume constancy elsewhere. That is, only an ever-declining growth rate in the nonhealth portion of the economy can support a relatively constant, above-average growth rate in health costs. It is this consideration, among others, that leads me to predict slower rates of growth in periods like now, when the predictions are again fairly high, even though, more generally, the lack of real budget constraints in health has historically led me to dispute predictions that tend to swing lower when some recent period has exhibited lower growth.

As more and more workers in different industries are required to accept negative cash wage increases to support higher health insurance costs, we do not fully know how that increased pressure will affect growth in health costs. Or policymakers, for that matter. The CMS actuaries must assume a continuation of current policy, no matter how unsustainable from a private or public perspective. Accordingly, they would be the first to admit that they are not projecting future health costs (despite the title of their article), only simulating what would happen to the health side of government and the economy under a set of policy assumptions whose merit they are not asked to assess.

Why Savings Don’t Accrue

The trend report, “National Health Spending by Medical Condition, 1996-2005,” is fascinating for what it reveals about how much growth there is in almost every category or condition. I also note how similar the growth rates are across many of the major spending categories (6, 6, 9, 6, 10, 7, 5, 6, 10, and 9 percent). This report also represents a step toward developing the input side of the input-output matrix, as I suggest above.

In that report, Charles Roehrig and colleagues state that “the ability to track national health spending by medical condition should help identify conditions that account for large shares of spending and growth and that, therefore, deserve particular attention in our quest to improve value, manage growth, and target prevention efforts” (emphasis mine).

I don’t disagree, but I do want to point out why even this type of development still is limited in how much, by itself, it can do to “manage growth,” at least in the aggregate

As Randy Bovbjerg and I suggested in Health Affairs in 2008, health reform has yet to deal with its original sin, which largely boils down to public and private insurance policies where we and our doctors, at no cost to ourselves, bargain with little budget constraint over what everybody else will pay.

When I examined a half-century of Bureau of Economic Analysis data, they demonstrated that growth industries with above-average growth in quantity of services delivered almost always exhibit below-average growth in the price of their services. Except, as you might guess, the health industry. Imagine if software or cell phones that were introduced in 2005 cost more in 2010 than 2005, and you’ll get an idea of how different the health industry operates than every other growth industry.

Yes, I know the ability to measure quality improvements is limited (almost in every industry, not just health), but even anecdotally, we witness numerous examples of price increases — or very limited price reduction — after some new drug or health procedure is introduced. This type of behavior simply would not be so easily observed in other growth sectors. Even if you dispute this history, the issue is still vital. We know that in the ideal, any future slowdown in health cost growth is going to be far more beneficial to us if it somehow plays out in prices rather than in lesser improvements in the quantity and quality of what we gets.

Why are improvements in information — including not just from his type of study, but from other ventures in electronic health records and comparative-effectiveness studies — limited in how much, by themselves, they can constrain health costs? If drug manufacturers can adjust by charging even more for the next new drug when there is some cutback in payments for an existing drug, or if providers can simply add to the number of diagnoses or diagnosis-related groups they cite for each patient, or cut back on the time they spend with each patient, or make any of a series of other adjustments, then the additional information will be limited in how much it helps manage growth.

Think of a balloon on which you push and make an indentation. Yes, you have made a difference at that spot. But the air has just moved elsewhere.

The bottom line is that there are limits on how much additional information, by itself, can help us control costs for the long-term. I must save for another time what happens when one violates the basic budget principle for a more level playing field for choosing, say, between education and health. Suffice it to say that medical condition spending breakdowns, like other necessary and important improvements in information, need some budget constraint to allow decisionmakers a place to channel that information effectively.

Note, by the way, how much more valuable a report on growth in spending by medical condition would be if we were able to match it up with some information on growth in incomes of providers dealing with these conditions (see first section above).

My bottom line is to congratulate the authors of two very fine studies — who, like any good researchers, succeed best when they remind us of how much more information we would like to have.